Articles | Volume 4, issue 1
Original research article
10 Jan 2018
Original research article |  | 10 Jan 2018

Evaluation of digital soil mapping approaches with large sets of environmental covariates

Madlene Nussbaum, Kay Spiess, Andri Baltensweiler, Urs Grob, Armin Keller, Lucie Greiner, Michael E. Schaepman, and Andreas Papritz

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Cited articles

Adhikari, K., Kheir, R., Greve, M., Bøcher, P., Malone, B., Minasny, B., McBratney, A., and Greve, M.: High-resolution 3-D mapping of soil texture in Denmark, Soil Sci. Soc. Am. J., 77, 860–876,, 2013.
AGR: Geoprodukt Geologische Rohstoffkarte ADT, Metadaten komplett, Amt für Gemeinden und Raumordnung des Kantons Bern, (last access: 4 April 2017), 2015.
Aitchison, J.: The statistical analysis of compositional data, Chapman & Hall, ISBN: 0-412-28060-4, 416 pp., 1986.
ALN: Historische Feuchtgebiete der Wildkarte 1850, Amt für Landschaft und Natur des Kantons Zürich, (last access: 29 March 2017), 2002.
ALN: Geologische Karte des Kantons Zürich nach Hantke et al. 1967, GIS-ZH Nr. 41, Amt für Landschaft und Natur des Kantons Zürich, (last access: 15 February 2015), 2014a.
Short summary
This paper presents an extensive evaluation of digital soil mapping (DSM) tools. Recently, large sets of environmental covariates (e.g. from analysis of terrain on multiple scales) have become more common for DSM. Many DSM studies, however, only compared DSM methods using less than 30 covariates or tested approaches on few responses. We built DSM models from 300–500 covariates using six approaches that are either popular in DSM or promising for large covariate sets.